Network usage data plays a critical role in revenue assurance and fraud detection. It provides essential insights into how consumers are utilising the network, how the network is performing, and any problems or issues related to network usage. This enables a Telco to reduce network revenue leakage, avoid unrecoverable losses and stop fraud.
Overview of Network Usage Data
Within the Telecommunications industry, we often refer to network usage data as Call Detail Records (CDRs). CDRs provide data on how users utilise a phone system, the internet, video calls, SMS, etc. CDRs provide hundreds of fields for each call record and information related to each call type. These CDRs capture information that includes the number that made the call, the number that received the call, the date and time of the call, the duration as well as usage and diagnostic information related to call quality, handset identification, the ID of the network equipment (cell tower) that facilitated the event, the reason for call terminations, and more.
You may be asking why this type of information is so important to a Telco? The answer lies in the value that this information provides. When utilised correctly, this data can be incorporated into reports where a business’s critical analytics and insights can be identified. These insights will provide the Telco with information related to network usage, capacity, billing, and performance, thus making it easier to identify any problems, issues, or opportunities, especially where revenue assurance and fraud detection are concerned.
The Role Network Usage Data plays in Revenue Assurance
In simple terms, revenue assurance is defined as a process that ensures that all products and services are billed as per the contract agreements with customers. This is done by ensuring that all operational departments have accurate data, related to billing and configuration integrity. This allows Telcos to make informed decisions, identify problems and develop improvements that positively impact profit, revenue, and cash flow.
A Telco generally has many different products, services, and business operations which are often siloed and don’t talk to each other. The sheer scale of these elements means that there are added complexities in managing each of these. This is where the chances of errors and revenue leakage increase. It often happens when a Telco is not able to identify incorrect billing because there are not enough checks and balances in place. As you can imagine, this poses a critical challenge for Telcos, especially since this directly impacts profitability.
CDRs play an essential role in stopping this kind of revenue leakage. This is because, when used correctly, the analytics and insights gained from CDR’s enable a Telco to identify problems related to network elements, billing, subscribers, network quality, incorrect links, network abuse, and more. These elements can affect a Telcos revenue and attribute to avoidable unrecoverable revenue losses.
The Role Network Usage Data plays in Fraud Management and Detection
Fraud within the Telecommunications industry continues to impact Telcos significantly. Different types of fraud and threats are recorded constantly, which means that Telcos need to ensure that they have the correct systems to manage and identify fraud to prevent these kinds of abuses.
When talking about fraud within this industry, we can refer to several different types, four of the most popular types include:
- Stolen Identities – also called SIM Jacking, criminals take control of a person’s SMS and phone calls by switching a phone number to another they are in control of to gain access to all OTP’s and SMS verifications in order to take over all customer accounts, including social media and banking.
- Subscription Fraud – occurs when fraudsters sign up for contracts using stolen IDs and stolen credit card numbers.
- SIM Box Fraud – also known as interconnect bypass fraud, takes advantage of a termination rate to make cheaper phone calls. These criminals use SIM cards from a local carrier and reroute international calls using a SIM box or GSM gateway, therefore making long-distance calls much cheaper for the callers. This type of fraud is estimated to cost telecom operators $2.7B in lost revenue per year.
- Wangiri – Wangiri telecommunications fraud involves striking curiosity in customers by calling them, letting the phone ring once, and hanging up. The customer will ring back, unwillingly calling an expensive premium number that the fraudsters control.
According to GSMA, Network fraud costs Telcos 1-2% of their revenue, on average, which impacts the profitability of Telcos dramatically. But by using CDRs you can drastically reduce this impact. You may be asking what CDRs have to do with fraud detection? The answer is everything. With the analytics and insights gained from CDRs, you can quickly uncover and identify abnormalities and different fraud patterns. This allows you to stop these abuses faster and more efficiently, reducing data misuse and preventing revenue losses caused by fraud.
Utilising CDRs effectively
From the above, it is clear that CDRs can play a significant role in revenue assurance and fraud detection, but this is only the case if your CDRs are accurate and reflect data related to all of your business areas. This is where Adapt IT Telecom’s CDRlive technology comes into play.
Although CDR data is valuable, the raw data as it stands does not make sense on its own. Adapt IT’s CDRlive platform utilises Artificial Intelligence and machine learning to turn these CDRs into valuable insights that can be used to improve Telco operations, performance, offerings, service delivery, and profitability. This platform collects data related to network elements, billing, subscribers, as well as other event record sources, to provide a holistic view of all network usage and operations across the business.
With this full visibility, Telcos are able to access reports and analytics in almost real-time, which will enable them to identify elements affecting network leakage, data usage, network quality, and more. Once these elements have been identified, the Telco can take the steps to rectify any identified problems to reduce revenue losses and fraud.
The CDRlive technology was recently implemented by a Telco Operator in Africa with 2.6 million active subscribers. This Telco was specifically looking for a platform that would enable them to easily identify, view, navigate, and investigate revenue leakage and fraud issues. Adapt IT team specifically put together a number of use cases that would help to identify potential problems and issues related to revenue leakage and fraud for this customer. The Telco would then be alerted to these and be able to view the accurate and available data on the user-friendly dashboard. The results of this included:
- Reduced investigations and response time.
- Near real-time monitoring and alerting.
- Consolidated operational and executive views.
- Easily identifiable root causes and problems.
- Accurate analytics, metrics, insights and data, which enhances decision making.
- Savings on revenue loss.
Network usage data in the form of CDRs play an essential role in providing Telcos with the insight needed to reduce revenue leakage, avoid unrecoverable revenue losses, and detect fraudulent activity. To ensure the accuracy of this, CDRs need to be organised in such a way that they reflect all the necessary network data that affects the different operational areas of the Telcos. Only with this consolidated view can you gain the analytics and insight necessary for revenue assurance and fraud detection. Adapt IT Telecom’s CDRlive technology does this and more. For more on CDRlive, download our whitepaper here.
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With over 20 years of experience in executive and operational management of Telecommunication technologies and services, Tertia is a Telecommunications Data Analysis Specialist. As a Specialist in Call Data Records and the CDRlive platform, she has practical experience in the design and implementation of Telecommunication data analysis and models. Tertia’s passion is to transform billions of seemingly unrelated data into a clear, informative picture – just like a painting.